Generative artificial-intelligence (GenAI) is not just the future—it’s already here, reshaping hundreds of industries and unlocking new possibilities for improvement and potentially step-change developments. For hardware product companies, integrating GenAI into existing workflows, development processes, and even the products they create presents unique challenges, but with the right approach, it also offers unparalleled opportunities for innovation, efficiency, and value creation. 

The New Disruptors: AI-First Startups Focused on Hardware Now smaller, agile teams are effectively leveraging GenAI, and nearly every new startup is an AI-first company. You can look at services like Enzzo, Flux, Vizcom, Zoo, Adam, Cofactr, Partsimony, Leo, and others as examples of how AI-first companies are focusing on unlocking significant gains in speed and innovation for hardware companies. With as little as a few million in funding, they are outpacing industry giants by harnessing the latest foundation models and AI innovations, free from the constraints of legacy systems. This allows them to approach solving problems in new ways, and for their customers, offering alternatives that are faster, easier to use, and cost less. The ability to scale change in these comparatively small ventures underscores the vast array of resources available and the democratization of AI-driven innovation. The Internal Adoption Gap: Curious Employees, Cautious Companies

While many companies and teams are eager to adopt GenAI, they often struggle with implementation strategies. Many employees are already experimenting with tools like ChatGPT, often with personal accounts on the side, while corporate policies sometimes lag, creating questions or concerns about whether it is approved for work, and limiting broader adoption. By proactively addressing the growing concerns around security while developing guidelines for the ethical development, use, and implementation of GenAI, it’s clear companies should effectively balance fostering innovation while mitigating risks to be part of this wave.

AI at Work: Real-world Examples from Design to Deployment Already many companies are experimenting with using GenAI as part of their internal workflows. McKinsey estimates GenAI in product research and design alone could unlock $60 billion in productivity. Flux cites a customer building agriculture devices and services that went faster and saved money by using its PCB design services. People are generating personas and interacting with them to better understand needs and define products in Enzzo, getting a wide variety of 3D renderings in Vizcom in seconds, and building out full CAD on the web using just text in Zoo or Adam, or smart ranking your supply chain quickly with Partsimony. In industries like automotive and IoT hardware, where precision and innovation are paramount, GenAI is proving to be an invaluable partner in the creative process. In the automotive world, Ferrari’s F80 hypercar used GenAI for the suspension design along with 3D metal printing technologies. GenAI is changing the speed of hardware product exploration, design and innovation, and shipping time to customers. Building GenAI-Enhanced Hardware Products, Not just Workflows We are also seeing hardware companies - small and large - adding GenAI as a feature to augment their hardware. From startups experimenting early like Rabbit and Humane to big tech from Apple Intelligence to Meta AI in Ray-Bans. The Meta Ray-Ban glasses shipped initially without a GenAI-feature, but Mark Zuckerberg personally called the lead of the program one weekend and suggested they add new functionality. Meta shipped the feature after the hardware was in market, giving users new ways to gain access to information - like providing information about what the user is seeing through their glasses. OpenAI and legendary product creator Jony Ive are even partnering on a new AI-powered hardware product. These companies point to the future of AI, and specifically, GenAI, as a widespread and key enabler in the hardware products we will buy and use.

One of the most exciting aspects of GenAI adoption is its potential to enhance human creativity and help people create better products faster. While effective usage requires skilled prompting or using a tool that abstracts it, learning how to interact with these systems unlocks new levels of productivity. One of the most powerful aspects of GenAI for creativity is that it accelerates early-stage ideation, empowering teams to generate and refine concepts more quickly. From fledgling to highly skilled teams, everyone can benefit from trialing and leveraging GenAI’s capabilities for their work.

Getting Started: A Playbook for Product Leaders

Successful integration of artificial intelligence technologies internally requires a strategic approach and a comprehensive educational program to ensure its effective and responsible implementation. For internal tools, GenAI excels at rapid experimentation, making sense of large data sets, software development, and doing real work for users, making it an invaluable assistant and asset. 

For integrating GenAI into products, there are pros and cons and it needs to be addressed responsibly like we are seeing from companies like Apple, Meta and others. By recognizing strengths and limitations, companies can set realistic goals and implement GenAI solutions that enhance efficiency without compromising precision or user trust.

The First Step Acknowledge that this is the future—and the time to embrace it is now. If you are a CEO/product leader, ask how might you and your teams begin to use GenAI in your daily work routines to do things faster and more efficiently than you have previously been doing, and then how might you use it to explore new product innovations. Define clear objectives and foster a culture that embraces GenAI as a powerful tool rather than a disruption. My friends at Pioneer Square Labs like to say, “The AI tools you use today are the worst they are ever going to be.” They aren’t perfect, but if you view and use them with the right lens you will gain productivity wins now, even as they get better.  Get Started

Exploring GenAI-driven solutions is key. Companies should embrace and test a range of solutions, from CoPilot to specialized hardware tools, and actively encourage teams to experiment with these technologies. Many of these services are going to be from AI-first companies, which means start up companies. Hardware teams demand both creativity and precision. While early GenAI tools might not meet all expectations on accuracy, pairing them with expert judgment quickly unlocks real value. A passionate internal AI champion—whether a CEO/VP, product lead, industrial designer, or business development manager—can play a pivotal role, inspiring adoption efforts and generating enthusiasm within the organization. 

Involve IT and Provide Usage Guidelines

Companies can begin testing using paid accounts to trial fast using non-company proprietary data and if the tool shows promise, can get IT involved. To ensure security, IT departments must rigorously vet AI tools, assessing data handling, encryption, and cyberattack vulnerabilities. A simple rubric - if you are using it free, it’s likely training on your data. A successful deployment involves structured training programs, hands-on onboarding sessions, and company-wide discussions to educate employees about the tool's capabilities and uses. Knowing it is approved to use is critical for employees who are responsible and don’t want to jeopardize the company's confidential information or their jobs. Clear usage guidelines are essential for responsible use, aligning with company or team goals. Ongoing support and monitoring, including regular employee feedback, ensure the GenAI tool remains effective and addresses potential issues promptly.

For large companies, overcoming internal resistance is part of the journey. While some team members may initially be skeptical, organizations that frame GenAI as an innovation catalyst rather than an immature technology or threat see the most success. It is crucial that strong leadership and open-minded experimentation encourage teams to engage meaningfully with GenAI, ultimately improving workflows and outcomes.

GenAI is Accelerating Internal Workflows and Product Timelines Now internal product teams that once spent months brainstorming and iterating can use GenAI to explore multiple variations quickly, refining the best ideas in record time and even testing against synthetic AI-generated customers to further refine them. Teams that are trying to understand supply chain availability have access to new tools like Partsimony and Cofactr, or use Leo to do engineering calculations faster. Many established product companies – think PC, camera, even B2B hardware makers, for example – are leveraging GenAI to explore and generate numerous product concepts, significantly reducing time and accelerating internal discussions and approval timing. McKinsey reports substantial productivity gains on shortening hardware product design life cycles. These examples are reinforcing GenAI’s potential to revolutionize hardware development. The human-AI synergy But GenAI’s true strength isn’t just in speed—it’s in augmenting human thinking and decision-making to make people more productive. As one industry executive put it, using GenAI is "the best tool to unblank a sheet of paper." It fuels ideation, accelerates innovation, and empowers teams to make more informed decisions. Ethan Mollick from Wharton recently released research with Harvard Business School on the “Cybernetic Teammate” based on studying Procter & Gamble product teams using GenAI. They found significant gains in employee productivity while also uncovering new insights about how using GenAI helps employees create more balanced solutions regardless of their professional background. More interestingly, they also identified findings in GenAI’s role as a teammate, which we will increasingly see more of from companies like Leo (engineering copilot) and Enzzo (PM assistant) providing GenAI teammates to help augment humans with a range of activities, including for product innovation. Conclusion

As GenAI adoption strategies evolve, companies must start. Start internally, empower your teams, and then bring into your hardware products for your customers. Regardless of company size, by embracing structured engagement, fostering internal champions and integrating GenAI into work, workflows, and products, companies can unlock GenAI’s full potential and drive to the ‘new normal’ of enhanced product innovation, GenAI-powered!